PLAIXUS
Inceptive Global Learning and OptimizatiOn is the Inceptive toolbox to train and serve Machine Learning models.
Datasets provided are used to train ML models for forecasting electricity production on hourly basis. Developed by Vodena doo for the GRIDouble project, part of the I-NERGY 2nd Open Call.
GRIDouble is a comprehensive energy management tool that completely automates the finding of optimal patterns in energy consumption and production in the case of facilities with renewable energy sources.
In the energy landscape that DSOs find themselves in today, predicting demand and the generation capacity of the systems to which they distribute becomes essential. This is mainly due to the injection of renewable energy among the consumers of the network...
AI4CZC platform is the Inceptive platform for energy forecasting.
The dataset provides energy consumption readings from a specific device, identified by UUID. The data captures detailed information, including the exact timestamp of the reading, energy consumed, and voltage, among other parameters. All readings are taken...
The Load Forecast Model is distinguished by its precision in predicting energy load demands, owing to its integration of advanced machine learning algorithms. Its cloud-hosted nature ensures scalability and adaptability, catering to both centralized and e...
A Java library to easily retrieve data from ENTSOE transparency platform.